Abstract:The first step of dermoscopic image analysis technology is image segmentation, and the result of segmentation will directly affect the subsequent processing. For dermoscopic images with background noise, blurred edges and uneven gray levels, a new hesitant neutrosophic set image segmentation method combined with level sets is proposed. In this method, the image is firstly transformed into the hesitant neutrosophic image by using the theory of hesitate neutrosophic set, in which the hesitate neutrosophic image is composed of three kinds of subsets (T, I, F), and the hesitant neutrosophic set image is used to highlight the target information and edge information of the image. Then, aiming at the shortcomings of the traditional DRLSE level set, a new edge stopping function is constructed, and the gray driving energy term is added. Finally, the ISIC (2018) dermoscopic image is segmented and tested through the improved DRLSE level set. The Jaccard Index values of the experimental results are all greater than 95%, and the mean square error (MSE), peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) all perform well, indicating that the proposed method can accurately and effectively segment the dermoscopic images with fuzzy edges and uneven gray level. This research lays the foundation for the processing and diagnosis of subsequent dermoscopic images.